1. Field of the Invention
The present invention relates to data processing methods for automatically monitoring and analyzing the actions of users of a web-based or other electronic catalog, and for providing associated notifications and content to such users.
2. Description of the Related Art
Various types of computer-implemented services exist for assisting users in locating and purchasing items from an electronic catalog. For example, some retail sales web sites provide notification services through which users can subscribe to be notified by email when an out-of-stock item becomes available. In addition, some auction sites provide a service for notifying auction participants by email when they have been outbid. While these types of notification services are helpful, they generally benefit only those who have expressly requested to be notified about, or have bid on, the relevant item.
Some web sites also provide limited-time discount offers to users. For example, Amazon.com's Gold Box feature allows a user to view a series of catalog items that are available at designated discount prices if purchased within sixty minutes of viewing each item. Once a user has viewed all items in the series, the user must wait a certain time period, such as one day, before viewing the next series of discount offers. The discount offers presented via the Gold Box feature are tailored to offer the user products in categories in which the user has not yet purchased.
Some web sites also provide services for assisting users in identifying catalog items that are related to the items they have viewed or purchased. For example, it is known in the art to monitor and analyze the browsing actions of a population of users to identify catalog items that are related by virtue of the relatively high frequencies with which they are viewed, purchased, or otherwise selected in combination. The item relationships detected through such analyses may be displayed to assist users in identifying items of interest, and may also be used to provide personalized item recommendations to users.